KR20190107109A - Computer-implemented system and method for generating and extracting user-related data stored on the blockchain - Google Patents

Abstract

A computer implemented system and method for providing user related data, such as reputation information, for users of a blockchain involved in transactions are described in detail. This method involves an approach that specifically evaluates the fulfillment of transactions in the context of the contract and then provides a record to the blockchain through reputation information. As a result, this reputation information can be retrieved at a later time. Similar reputation information for other transactions can be retrieved based on the use of a hash of the master public key for the user and linked to the same user. The aggregated reputation information may be computed from the pieces of retrieved reputation information.

Description

Computer-implemented system and method for generating and extracting user-related data stored on the blockchain

The present invention relates generally to computer implemented systems and methods, and more particularly to computer implemented systems and methods for providing data for a user associated with transactions. The present invention is particularly suitable for use in providing data such as scores, accuracy or quality measurements with respect to aspects of transactions on a blockchain, but is not limited thereto. For example, it provides reputation information for users involved in transactions, and in particular, but not limited to, providing reputation information for users of smart contracts implemented on the blockchain.

In this document, the term 'blockchain' is used to cover all forms of electronic, computer-based, distributed ledger. This includes licensed and unauthorized ledgers, shared ledgers, and variants thereof, but is not limited to blockchain and transaction chain technologies. The most popular application in blockchain technology is Bitcoin ledger, but other blockchain implementations have been proposed and developed. Although bitcoin may be mentioned for convenience and explanation herein, it is to be understood that the invention is not limited to use as a bitcoin blockchain, and that other blockchain implementations and protocols are within the scope of the invention.

Blockchain is a consensus-based electronic ledger that is implemented as a computer-based decentralized distributed system of blocks composed of transactions in sequence. Each transaction is a data structure that encodes a transfer of control of a digital asset between participants in a blockchain system and includes at least one input and one output. Each block contains a hash of the previous block so that the blocks are linked together to create a permanent and immutable record of all transactions written to the blockchain since the beginning. Transactions include small programs known as scripts embedded in their inputs and outputs, which indicate how and by whom the output of the transactions can be accessed. On the Bitcoin platform, these scripts are written using a stack-based scripting language.

In order for a transaction to be written to the blockchain, it must be "validated". The network node (miner) rejects invalid transactions in the network, and performs work to ensure that each transaction is valid. Software clients installed on the node perform validation work on unspent transactions (UTXOs) by executing locking and unlocking scripts. If the execution of the lock and unlock script evaluates to TRUE, the transaction is valid and the transaction is written to the blockchain. Therefore, in order for a transaction to be written to the blockchain, i) it must be authenticated at the first node receiving the transaction, and if the transaction is valid, the node forwards it to another node in the network; ii) added to a new block built by the miner; iii) mined, ie added to the public ledger of past transactions.

Although blockchain technology is most widely used for cryptocurrency implementations, digital companies are beginning to explore the use of data that can be stored on the blockchain to implement bitcoin-based cryptographic security systems and new systems. . It would be very useful if the blockchain could be used for automated tasks and processes not limited to the realm of cryptocurrency. These solutions can take advantage of the blockchain (e.g., permanent, temporal proof recording of events, distributed processing, etc.) while being used more widely in their applications.

One area of current research is to use blockchain to implement "smart contracts." These are computer programs designed to automate the execution of machine-readable contracts or terms. Unlike traditional contracts written in natural language, smart contracts are machine-executable programs that contain rules that can process input to produce results, and actions can be performed according to the results.

Another area related to blockchain is the use of 'tokens' (or 'color coins') to represent and convey real entities through the blockchain. Potentially sensitive or secret items may be represented as tokens with no identifiable meaning or value. The token thus serves as an identifier that allows the actual item to be referenced in the blockchain.

Various prior art methodologies are known for managing user related data such as reputation data or credit information in a network. Examples of such prior art methodologies are briefly described below.

Chris Pacia et al. The presentation of “OpenBazaar-Ratings, reviews and reputation” launches a blockchain-based rating system. In slide 55, when an item is received, Buyer creates a rating just before releasing funds to Vendor. Rating data is attached to the Ricardian contract. The rating data includes scores provided by the buyer based on the following parameters: feedback; quality; detailed description; Delivery time; customer service; And reviews. In slide 63, OP_RETURN has a vendor's Globally Unique Identifier (GUID), which is used to filter the associated multiple signed transactions from the blockchain when scanning the rating. It also indicates that the vendor's GUID signature in the scriptsig of these tagged multi-signature transactions is considered "validated proof that the vendor is involved in the transaction" only.

It should be noted that in the system disclosed in OpenBazaar, the rating data is provided by the Buyer. This rating information can in principle be abused (e.g. by a competitor putting poor rating information). To prevent abuse of the rating system in OpenBazaar, the system only uses transactions signed by the vendor, thus representing the actual transactions. However, this prevents competitors from legally purchasing a product or service in a transaction signed by the vendor but does not provide poor rating information to prevent a third party from purchasing the product or service from the vendor.

WO 2015/085393 discloses a rating system for evaluating the transaction history of a digital currency. The rating system includes a storage system for storing transaction information of the digital currency; An interface for receiving an identifier of at least one account associated with a digital currency and a request to evaluate a transaction history of the at least one account; And a processor in communication with the storage system and the interface. The processor identifies a transaction of the at least one account from the transaction information stored in the storage system and evaluates the destination of the identified transaction to generate a rank for the at least one account. It is further disclosed that the rating system may assess the amount and age of the identified transactions, and that the rating system may be useful for, for example, a peer-to-peer digital call. The storage system does not appear to include a blockchain, only user-specific transactions include the amount, date and destination of the identified transactions.

US2006149745 discloses a system and method for providing feedback data within a distributed feedback system of an electronic commerce system. Feedback data describing an e-commerce transaction is generated by buyers of goods and services and sellers of the goods and services. Feedback data is stored and managed in a set of feedback servers comprised of peer-to-peer (P2P) networks of distributed devices. The feedback data consists of a grouping of feedback data stored on a database repository associated with each P2P network node. Buyers and sellers can retrieve feedback data from these distributed data sources to obtain reputation data associated with the parties that propose new transactions for goods and services. No blockchain system is disclosed in which user related data is transmitted, stored, retrieved and extracted.

US2015302400 discloses a method comprising monitoring a distributed cryptocurrency reputation system and a cryptocurrency public ledger. The current cryptocurrency transaction is detected in the cryptocurrency public ledger, so that a reputation marker can be assigned to both the payer and the payer involved in the current cryptocurrency transaction. At least some of the reputation markers are then determined to be transferred from the payer to the payer and from the payer to the payer. When a request for reputation information for a payee or payer is received, information may be provided relating to transferring at least some of the reputation marks from the payer to the payer, or from the payer to the payer.

CN106230808 discloses storing personal credit information from many different institutions on the blockchain.

A problem with existing systems and methods for providing data, such as reputation information for system users, is that the systems and data are vulnerable to attack and manipulation or are inadequate for implementation in distributed systems.

Accordingly, it is intended to provide a solution aimed at more robust systems and / or methods against attack and manipulation.

Accordingly, it is intended to provide a solution aimed at systems and / or methods suitable for implementation in distributed systems.

Accordingly, it is intended to provide a solution aimed at a system and / or method suitable for implementing a blockchain or a bitcoin blockchain.

In terms of generating user-related information, we will provide a more objective solution.

Another object is to provide an effective and efficient way to create, store and retrieve user related data in the blockchain.

A system that improves this is disclosed herein. The invention is defined by the appended claims and / or features, options and possibilities described herein and / or within this document.

A method of computing aggregated user related data according to a first embodiment of the present invention

a. Constructing a user related data transaction, wherein the user related data transaction comprises an expression of user related data from a previous transaction associated with a user;

b. Broadcasting the user-related data transaction to the blockchain;

c. Repeating steps a) and b) for the plurality of previous transactions and / or the plurality of users;

d. Selecting a user for which aggregated user related data is required to obtain a selected user;

e. Creating a filter associated with the selected user;

f. Retrieving a blockchain for a user related data transaction to which the filter is applied;

g. Computing aggregated user related data for the selected user from the user related data transactions to which the filter is applied.

This method can provide that the aggregated user related data is aggregated reputation information. The user related data transaction may be a reputation transaction. The user related data transaction may include a representation of the fulfillment of a previous transaction involving the user. The user related data from the previous transaction may be a representation of the fulfillment of the previous transaction with respect to the user.

This method allows the computed aggregated user related data to make a decision, preferably through evaluation, and most preferably an action and / or modification can be made according to the decision. One or more assessments may be made. One or more decisions may occur. One or more operations may be performed. One or more modifications may be made.

The computed aggregated user related data may be evaluated according to thresholds and / or ranges. The value for the first side of the threshold can cause a first determination. The value for the second side of the threshold may result in a second decision and may preferably be different from the first decision. In-range values can cause a first determination, and out-of-range values can cause a second determination.

Decisions and / or actions and / or modifications may change one or more inputs for one or more additional transactions, such as blockchain transactions. Decisions and / or actions and / or modifications may change one or more outputs from one or more additional transactions, such as blockchain transactions. Decisions and / or actions and / or modifications may alter the decision finite automaton (DFA), for example the DFA implements one or more additional transactions.

Decisions and / or actions and / or modifications may provide feedback for modifying and / or optimizing the performance of a DFA, eg, DFA.

Decisions and / or actions and / or modifications may provide feedback for modifying and / or optimizing the design and / or production and / or storage and / or distribution and / or consumption of services and / or products.

Decisions and / or actions and / or modifications provide feedback for modifying and / or optimizing processes such as those for the design and / or production and / or storage and / or distribution and / or consumption of services and / or products. can do.

Decisions and / or actions and / or modifications may provide feedback for modifying and / or optimizing a contract, such as a smart contract.

User related data may be time. The time may be the time at which the event occurred. An event can be the completion time of a transaction or state transition or blockchain transaction originating from DFA and / or the state change time in DFA when implementing a DFA operation.

User related data may be a representation of accuracy and / or precision. Accuracy and / or precision may be obtained from measurements entered into, used by, or output by the DFA. The measurement may be one or more physical parameters such as size, volume, shape, mass, area or other quantitative value. Accuracy and / or precision for physical parameters, for example a predetermined acceptable range, can be evaluated and recorded. The assessment may be relative to actual values and / or targets and / or deviations from actual values. The evaluation may be the presence or absence of a defect or other undesirable features.

User related data may be associated with physical forms. The physical form may be related to the physical form entered into, used by, or outputted by the DFA, such as, for example, the physical form itself and / or other quantitative values such as size, volume, shape, mass, area, etc. It may be a quantified physical form. User related data may be a type of product or service.

User related data may be related to quality, such as, for example, goods and / or services provided using transactions, potentially transactions implemented via DFA. Quality can be related to the implementation of the transaction itself. The quality may be specification quality and / or conformance quality. Quality can be used in the quality management process by providing feedback that affects one or more variables in the next transaction and / or the next form and / or implementation by the DFA. Feedback is defective; issue; fault; Failed task; There may be one or more of the failed state transitions. Quality may be used in the quality management process by providing feedback that affects the design and / or operation in the next transaction and / or the next form and / or implementation by the DFA in the next transaction. The quality control process may be a quality assurance process. Feedback is the intensity of the process and process steps; Stability of processes and process steps; It can affect one or more of the formats of processes and process steps. Feedback may increase the extent to which a transaction will fit in purpose and / or for the first time in future transaction configurations.

User related data may relate to a user's ability, for example, to be able to complete a common, potentially implemented transaction through part of a transaction and / or DFA. A capability can be a record of one or more of the following: evidence of competence; Evidence of knowledge; Evidence of skills; Evidence of experience; Evidence of qualifications; Evidence of certification; In particular, evidence of an assessment of one or more of these. Ability is a member of an organization and / or regulatory body; Endorsement and / or approval by a third party, such as a regulatory body or a trade body; It may be one or more of being present in a third party operating register.

In the context of contracts that can be potentially represented / implemented by DFA, contracts can be associated with various financial instruments. Potential financial instruments may include cash, deeds of ownership, and contractual rights (eg bonds) to receive or provide cash. Potential financial instruments may include cash instruments and potentially include one or more of the following: shares; Securities; Bills; Stocks; Options; Futures; Market valued assets. Potential financial instruments may include derivatives, and may potentially include one or more of the following: assets; Indexes; Interest rates; Loans; Deposits; Certificates of deposit; Fabric spot rates; Spot exchange rates.

Computer-implemented systems and methods are provided for providing user related data, such as reputation information for users of a blockchain involved in a transaction. This method involves, in particular, the approach of evaluating the performance of a transaction in the context of a contract and then recording it on the blockchain with reputation information. As a result, this reputation information can be retrieved late. Similar reputation information for other transactions can be retrieved and linked to the same user, for example based on the use of a hash of the master public key for the user. The aggregated reputation information may be computed from the pieces of retrieved reputation information.

In a preferred embodiment, in particular in the context of the contract, evaluation and record provision can be implemented using the decision finite automerton (DFA). This method allows DFA to configure and implement smart contracts for each user involved in each smart contract, as well as to consider the degree of fulfillment of the terms of the smart contract. Therefore, DFA generates reputation information about each user of each smart contract. In the example of a derivative, this is actually credit rating information. DFA allows this reputation information to be published and stored on the blockchain.

Thus, according to some configurations, user-related data, such as ratings information, is generated by the system itself rather than by the user. One example of such an automated system is the use of DFA described above. In principle, however, this can be implemented by an automated blockchain system in which a system other than a user provides rating data. For example, rating data may be generated by the blockchain system depending on how the user meets the conditions when implementing the digital smart contract on the blockchain system. This methodology provides more objective data compared to user input data and is generated and stored in a more efficient and reliable manner.

The method may further provide one or more of the following:

a. Defining a transaction between at least one user and at least one other user;

b. Executing the transaction;

c. Providing a user related data representation, such as a user fulfillment representation, by providing user related data from the transaction, such as a representation of the fulfillment of a transaction, for at least one users or at least one other users;

Provide a user related data representation, such as a user fulfillment representation, for use in constructing a user related data transaction, such as a reputation transaction, including a user related data representation, such as a representation of the fulfillment of a previous transaction involving a user. do.

According to a second embodiment of the present invention, there is provided a method of creating a record of user related data comprising the following steps:

a. Defining a transaction between at least one user and at least one other user;

b. Implementing the transaction;

c. Providing a user related data representation by providing user related data from the transaction for at least one user or at least one other user;

d. Constructing a user related data transaction comprising the user related data representation;

e. Broadcasting a user related data transaction to the blockchain.

This method may provide that user related data is reputation information. User-related data from a transaction may be a representation of a transaction's performance with respect to the user. The user related data transaction may be a reputation transaction. The user related data transaction may include a representation of the fulfillment of a previous transaction involving the user. The user related data representation may be a user fulfillment representation.

The second embodiment of the present invention may include any of the features, options, and possibilities presented in the first embodiment of the present invention.

According to a third embodiment of the present invention, a method of computing aggregated user related data is provided, the method comprising:

a. Selecting a user for which aggregated user related data is required to obtain a selected user;

b. Creating a filter associated with the selected user;

c. Retrieving a blockchain for a user related data transaction to which the filter is applied;

d. Computing aggregated user related data for the selected user from the user related data transactions to which the filter is applied.

This method can provide that the aggregated user related data is aggregated reputation information. The user related data transaction may be a reputation transaction. The user related data transaction may include a representation of the fulfillment of a previous transaction involving the user. The user related data from the previous transaction may be a representation of the fulfillment of the previous transaction with respect to the user.

The third embodiment of the present invention may include any of the features, options, and possibilities presented in the first embodiment of the present invention.

According to a fourth embodiment of the present invention, a computer-implemented system configured to implement the method of the first embodiment of the present invention includes a system potentially configured to perform any of the features, options, and possibilities presented elsewhere in this document. .

The system may further include:

a. User digital wallet;

b. At least one computing agent configured to implement DFA through a blockchain;

c. Blockchain Platform.

The fourth embodiment of the present invention may include any of the features, options, and possibilities presented in the first embodiment of the present invention.

According to a fifth embodiment of the present invention, a computer-implemented system set up to implement the method of the second embodiment of the present invention, potentially a system set up to perform any of the features, options and possibilities presented herein.

The system may further include:

a) at least one computing agent configured to implement DFA through a blockchain;

b) blockchain platform.

The fifth embodiment of the present invention may include any of the features, options, and possibilities presented in the first embodiment of the present invention.

According to a sixth embodiment of the invention, a system is set up to implement the method of the third embodiment of the invention, preferably a computer implemented system, potentially a system set up to perform any of the features, options and possibilities presented herein. It includes.

The system may further include:

a. User digital wallet;

b. At least one computing agent configured to implement DFA through a blockchain;

c. Blockchain Platform.

The sixth embodiment of the present invention may include any of the features, options, and possibilities presented in the first embodiment of the present invention.

Therefore, according to the present invention, the following options, possibilities and features may be provided or further provided.

The present invention can be provided in particular also in general, in connection with the first, second, fourth and fifth embodiments of the present invention. The term reputation information may be replaced with the term user related data in the present application. Reputation transactions may be replaced with the term user-related data transactions in this application. The representation of the fulfillment of a previous transaction can be replaced by the term representation of user related data.

The user fulfillment expression can be defined as a fulfillment score that quantifies the degree of fulfillment of a transaction by the user. The user fulfillment representation may reflect whether the transaction is complete. The user fulfillment expression may be a fulfillment value. The user fulfillment representation may be a fulfillment score, for example a binary score.

The reputation transaction further includes attribution information for the user with which the user fulfillment expression is associated. The attribution information for the user may be an address such as a bitcoin address for the user. The attribution information can be a signature script or a hash thereof for the user. The attribution information for the user may be an address, such as a bitcoin address for the user, and / or a signature script or hash thereof for the user. Attribution information may come from deterministic key generation performed for and / or on behalf of the user.

The reputation transaction may further comprise a transaction type for the transaction for which the user fulfillment representation has been obtained. The transaction type can describe the content of the transaction in detail. The transaction type may describe in detail the transaction template used. The transaction type may be a contract type, for example a smart contract type. The transaction type may be one of a list of notifications of the transaction type according to the transaction type.

The user fulfillment representation may be included in the metadata of the reputation transaction. User fulfillment representations and / or attribution information and / or transaction types may be included in the metadata of reputation transactions.

The reputation transaction may be a Pays To Script Hash (P2SH) transaction. The reputation transaction may be a multisignature transaction. Reputation transactions can be delivered to addresses controlled by third parties, for example, controlled by DFA. Reputation transactions can send dust.

The reputation transaction may implement FIG. 1. A redeem script for a reputation transaction may implement FIG. 2.

Reputation transactions can be implemented by decision finite automaton (DFA).

The method or system may include using a finite automaton to determine one or more of the following: define a transaction; Implement transactions; Provide an expression of fulfillment; Configure reputation transactions. The method or system may include using a common decision finite automaton (DFA) to define the transaction, implement the transaction, provide an expression of the fulfillment, and construct a reputation transaction.

One or more transactions may be a contract, for example a smart contract.

The present invention, in particular with respect to the first, third and sixth embodiments of the present invention, may also generally further provide one of the following.

The user may be selected from the users providing the transaction. The user may be selected by the selection user. The plurality of users may be selected by the selection user, for example. The selection user may be a user who considers starting one or more transactions.

The selection can be made using the user's digital wallet. The digital wallet may be provided with an interface for user selection. The digital wallet may be provided with an interface for display of aggregated reputation information and / or its further processed form.

Computing aggregated reputation information may be computed for one or more or all selected users.

The filter may be configured by obtaining an address hash from the selected user and / or a signature script from the selected user. The filter may be configured from an address hash resulting from the selected user's public key and / or a signature script resulting from the selected user's public key. The filter may be configured to provide a hash of the master public key of the selected user.

The method and / or system may further provide a user access to the blockchain and / or parse the blockchain.

The method and / or system may further provide that reputation transactions in the blockchain are considered to use filters. Preferably, in order to collect all reputation transactions picked up by the filter, for example to collect all reputation transactions including metadata picked up by the filter, most preferably the master public key for the selected user and It is to collect all reputation transactions picked up by the filter with respect to all descendant public keys therefrom.

Further processing may be applied to the aggregated reputation information, which further computes one or more of the following: numerical reputation score; Reputation scores; Reputation rating for other users.

The aggregated reputation information and / or its further processed form may be computed at the time of selection and / or as a suggestion from the user and / or before any selection and / or before a transaction proposal by the user.

The method for computing the aggregated reputation information may further include presenting the aggregated reputation information to a user, particularly a user whose wallet has computed the aggregated reputation information.

The method of calculating the aggregated reputation information may provide a method further comprising the step of the user making a decision, wherein the determination includes consideration of the aggregated reputation information. The decision may include a decision to start a transaction with the selected user.

The method of computing the aggregated reputation information may provide a method further comprising the step of the user and / or the selected user performing the action. The action may include providing information to the selected user; Receiving information from the selected user; Producing, by the selected user, a product for the user; Producing goods for the user selected by the user; Providing a product to a user by the selected user; Providing a product to a user selected by the user; The selected user sending, shipping or shipping the goods to the user; The user may include one or more of sending, shipping or shipping the goods to the selected user. The goods may be services and / or goods.

These and other embodiments of the invention will be apparent from and elucidated with reference to the embodiments described herein. Embodiments of the invention will now be described by way of example only and with reference to the accompanying drawings:
1 illustrates an implementation of a bitcoin transaction;
2 illustrates a Bitcoin transaction redeem script associated with FIG. 1 Bitcoin transaction;
3 shows the validity of links and transactions between transactions;
4 illustrates the flow of information from a transaction to a blockchain and into a wallet inquiry;
5 shows an overview of a system in which the present invention may be included;
6 illustrates a blockchain based DFA implementation.

The proposed invention is an implementation of a user related data recording system on a blockchain, more specifically on a bitcoin blockchain, and recording and processing user related data from the blockchain.

This method includes or provides an approach for evaluating user related data, and provides its record on the blockchain through user related data records.

In a preferred embodiment, evaluation and record provision can be implemented using crystal finite automaton (DFA). In the detailed example presented below, this is illustrated in a particular embodiment featuring a peer-to-peer derivatives trading platform, but other situations in which user-related data may also be applicable.

This method allows DFA to set up and enable the implementation of a transaction for each user involved in each transaction, as well as to consider user-related data arising from the transaction. Therefore, DFA generates user-related data in each transaction. DFA ensures that this user-related data is published and stored on the blockchain.

As a result, this user related data can be retrieved late. Also, as discussed below, similar user related data for other transactions can be retrieved and linked to the same user. In a preferred embodiment, this is based on the use of a hash of the master public key for the user. The aggregated user related data can be processed to give a user value for that user. The user value can then be used for subsequent evaluation and / or determination and / or modification.

In one embodiment, each user can use their Bitcoin wallet to retrieve user related data from the blockchain and then process the aggregated user related data, which can be displayed to the user via the wallet interface. This provides the user, substantially the customer user, with useful information about the counterpart user and the vendor user, which helps the user decide whether to participate in the provided transaction, among other possible benefits.

The solution provided is powerful, efficient, distributed and anonymous.

The proposed invention offers the following potential advantages:

Distributed to prevent large single points of failure and not to be vulnerable to attack;

No fees (usually only small transaction fees are expected in the Bitcoin protocol);

* Anyone who is global and can access the Internet at any time;

* Transparent, so anyone can see when data is written to the blockchain;

* Immutable, so once data is written to the blockchain it cannot be changed; And

Decentralized data recording, storage and retrieval system.

The implementation described in detail below provides for an important type of user related data in the context of reputation, but the invention can be applied to a wide range of user related data.

User-related data arises as a result of input to the blockchain transaction (e.g. user's presence and participation) and as a result of output to the blockchain transaction (e.g. user's influence on behavior and result) They allow user-related data to be processed, and user-related data evaluations enable to obtain user-related data worth being written to the blockchain (in a user-related data blockchain transaction). Thus, these individual pieces of user related data are readily available on the blockchain for subsequent retrieval and collection to provide aggregated user related data. This aggregated user-related data can be subject to processing. Treatment can lead to a variety of subsequent steps, including:

Potential evaluation of aggregated user related data; And / or

One or more decisions based on aggregated user related data; And / or

Modifications to future blockchain transactions or process variables, potentially impacting future blockchain transactions

Decisions and / or modifications can potentially improve future transactions and / or have a successful or more successful outcome compared to previous transactions.

In various embodiments, for example, user related data may be related to time. This may be the time when the blockchain transaction is completed due to DFA and / or the time when the state changes within DFA when implementing a DFA operation. Depending on the work of DFA, there may be several such times. Retrieval of multiple records of such user related data, including time, may be used to optimize the performance of the DFA, including the act of analyzing and / or implementing the use of DFA (as aggregated user related data). This includes optimizing the timing of services or products passing through the task, for example to improve process capacity. Optimization can be related to people approaching location and the like by changing the timing by controlling variables in a task. The time may provide information about the reliability of the work, the circumstances under which maintenance or service should be provided, etc.

In various embodiments, for example, user related data may relate to accuracy and / or precision. Thus, user related data regarding the accuracy and / or precision of user contributions can be collected and recorded. Accuracy and / or precision may relate to physical parameters such as measurements, such as size, volume, shape, mass, area, or other quantitative values, entered into, used by, or output by the DFA. Thus, in the context of DFA implementing a screening process to accept or reject a product or service, physical parameters may be considered. The accuracy or precision for the physical parameters, for example some acceptable range, can be evaluated and recorded. The evaluation may be for actual values, or may be deviations or errors for targets or actual values, and the like. The evaluation may be the presence or absence of a defect or other undesirable feature. For example, these multiple results may be considered together (as aggregated user-related data) to reveal rejection rates for multiple processes and / or to provide feedback on the control of those processes to improve future processes.

In various embodiments, for example, user related data can be associated with a physical form. Thus, user related data about the physical form of user contribution can be collected and recorded. A physical form is associated with the quantification of a physical form, such as, for example, the physical form itself and / or size, volume, shape, mass, area, or other quantitative value, entered into, used by, or output by the DFA. Can be. Thus, in the context of DFA that implements logistics operations, physical form may be considered. The particular physical form may affect or control the operation within the logistics operation, for example, it may be the maximum mass (as aggregated user-related data) that can be processed at a specific sized unit and / or inventory level. Similar principles may apply to user-related data that is a type of product or service. Thus, user related data may reflect outgoing sales and incoming supplemental supplies for the product to provide inventory levels (as aggregated user related data).

In various embodiments, for example, user related data may relate to the quality of goods and / or services provided using, for example, a transaction, potentially a transaction implemented through DFA. Quality can be related to the implementation of the transaction itself. The quality may be specification quality and / or conformance quality. Quality may be used in the quality control process, for example, by providing feedback that affects one or more variables in subsequent forms and / or implementations by the DFA for transactions and / or DFAs. The feedback may be present or absent one or more of the following: a defect; issue; fault; Failed task; Failed state transition. Quality may be used in the quality management process by providing feedback that affects the design and / or operation in the next transaction and / or the next form and / or implementation by the DFA in the next transaction. The quality control process may be a quality assurance process. Feedback is the intensity of the process and process steps; Stability of processes and process steps; It can affect one or more of the formats of processes and process steps. Feedback may increase the extent to which a transaction will be fitted for purpose and / or first in a future transaction configuration.

In various embodiments, user related data may relate to a user's ability to complete a general, potentially implemented transaction, eg, as part of a transaction and / or via DFA. A capability can be a record of one or more of the following: evidence of competence; Evidence of knowledge; Evidence of skills; Evidence of experience; Evidence of qualifications; Evidence of certification; In particular, evidence of an assessment of one or more of these. Ability is a member of an organization and / or regulatory body; Endorsement and / or approval by a third party, such as a regulatory body or a trade body; It may be one or more of being present in a third party operating register.

In the context of contracts that can be potentially represented / implemented by DFA, contracts can be associated with various financial instruments. Potential financial instruments may include cash, deeds of ownership, and contractual rights (eg bonds) to receive or provide cash. Potential financial instruments may include cash instruments and potentially include one or more of the following: shares; Securities; Bills; Stocks; Options; Futures; Market valued assets. Potential financial instruments may include derivatives, and may potentially include one or more of the following: assets; Indexes; Interest rates; Loans; Deposits; Certificates of deposit; Fabric spot rates; Spot exchange rates.

In the context of a reputation system, user related data may be reputation information; And / or user related data transaction considerations may include evaluating the performance of the transaction; And / or the transaction may be a contract; And / or the aggregated user information may be aggregated reputation information; And / or the user value may be a reputation indication or score.

In the context of reputation, there are a variety of other situations where benefits arise from the use of reputation information associated with the public key. What reputation information or score means depends on the situation before and after. For example, this may be a score about playing an online game.

Reputation information, such as reputation scores, may be applied to hotels, restaurants, e-commerce sellers, contractors or colleagues. This can be applied at the company, department, team or individual level. It can be applied to all your products (services or goods) or to a set of products or a single product. For example, the correct data can be used to calculate the h-index, the scientific research impact index.

Reputation information, such as reputation scores, can be integers or real numbers. This can be weighted by recency. This may be an absolute rating or a ranking for peers.

As illustrated above, the principles of the present invention can be applied to a wide range of data relating to a user. The following detailed implementations are provided in the context of reputation as an important type of data, but the present invention does not limit the scope or implementation thereof, as the present invention is implemented similarly for other data.

Trust is the foundation of many aspects of social and economic life. Just as money is a form of real capital, trust is very important as a form of social capital. But how do you learn to trust someone you don't know but wants to trade over the Internet?

Reputation systems are programs that allow users to evaluate each other in an online community to quantify trust and encourage credible behavior through reputation.

Reputation systems are important for distributed applications where users must trust each other, such as e-commerce websites. Reputation measures how much a community trusts you and is calculated based on previous transactions and interactions with other users of the community and / or ecosystem.

One aspect of reputation can be measured by fulfilling a contract with other users and counterparts. The higher your reputation, the higher your credibility on the network. This encourages interaction with you. Also, due to the user's reputation online, most users will choose to be more honest in the network.

Reputation systems compute and publish reputation information. Reputation information can take many forms such as scores, credit ratings, credit scores, ratings. Reputation information may be associated with a series of services.

Reputation has an excellent track record in facilitating collaboration in a wide variety of environments, such as online marketplaces such as eBay or blockchain-based auctions. Thus, it is not surprising that many peer-to-peer systems have adopted some form of reputation system to reward their peers for good and / or punish bad behavior.

However, there are issues regarding the reliability, vulnerability to attack or manipulation of such reputation systems, and the breadth of situations available.

Certain embodiments described herein relate to P2P derivatives, such as options, futures or futures trading in the Bitcoin blockchain as part of the P2P derivatives reputation ecosystem. In this particular embodiment, DFA provides reputation information to the blockchain, but the user's wallet generates aggregated reputation information and then processes it as a quantified reputation, which is a measure of trust to provide to the user.

An implementation of the invention is described by the following steps:

Generation of a transaction including attribution information;

Processing and recording reputation transactions including reputation information on the blockchain, along with attribution information;

Extraction of attribution information for the selected user and consequently reputation information for the selected user by the customer user's wallet;

Processing reputation information to provide aggregated reputation information, thereby obtaining a quantified reputation by a customer's wallet.

Source of Vendor Wallet and Attribution Information

For example, based on derivatives, there may be a set of user-provided contracts that other users can select. The user providing the contract is designated as the vendor user and the user selecting the contract is designated as the customer user for ease of identification. Of course, since both users can provide and receive within the terms of the agreement, and the agreement may involve more than one user, this designation does not limit the scope of the present invention.

The vendor user has a wallet, and the vendor user's wallet contains the information needed to carry out the transaction. This includes public and private key pairs required for transactions such as contracts. The vendor's digital wallet acts as a container for the provision of private and public keys as part of the software and is typically implemented as a structured file or a simple database.

A common way of generating pairs of keys is deterministic key generation. This makes it easy to generate many keys from a single "seed." Production uses the seed to generate a master key. The master key can be used to generate a series of child keys, and each child key can generate a series of grandchild keys for generations. All keys are linked in a hierarchy. In order to create an entire hierarchy of keys, only one single master key is needed.

Using deterministic key generation and hierarchical deterministic key generation has many advantages and encourages its adoption and use. Thus, the characteristics upon which the present invention is based exist in many of the keys in use.

More details on the appropriate approach for generating keys in this way can be found in the method described in the BIP0032 standard, Wuille, P. (2012), BIP 32: Hierarchical deterministic wallets , GitHub.

DFA implementation transaction

As mentioned above, this embodiment relates to a smart contract that includes configuration and performance by relevant users, along with the role of the present invention on reputation information. Determination Finite Automerton (DFA) represents one way to execute smart contracts for each user participating in P2P derivatives trading through Bitcoin blockchain.

More information on using DFA in smart contract implementation is provided in the Use of a DFA in Smart Contracts section provided at the end of this document.

Although we used DFA here, it is a useful tool for managing the status of (financial) contracts, so we can add the functionality of the present invention to the Bitcoin wallet without using DFA.

Many users can participate in contracts that are structured and implemented using DFA. Each user is associated with a pair of private and public keys that are used to facilitate a transaction. The previous section explains that they relate to master keys because they can be generated by deterministic wallets.

In the case of a vendor user, the seed is used to generate a master private key, the master private key is used to generate the master public key, and the master public key is used to generate other public keys. The vendor user's wallet selects one of the other public keys to facilitate the transaction represented by the contract. The recipient vendor user must provide the bitcoin address.

Bitcoin addresses are obtained by taking another public key to be used and applying it to a cryptographic hashing algorithm to obtain a hash of the other public key. More specifically, this is done by operation of SHA256 hash operation and RIPEMD160 hash. Hashes based on other public keys are typically encoded using Base58Check before actual use, such as bitcoin addresses for other public keys for use in contracts into transactions.

When constructing a contract, the implementation and results of the contract occur over time. From the results, it can be seen whether User X involved in the contract has met the conditions imposed by the contract or whether User X has not met the conditions imposed by the contract. Since these contracts are complex and may involve multiple users, the outcome of implementation may be visible to all parties.

In addition to the configuration, implementation, and outcome of a transaction, DFA may implement additional transactions to reflect the observed position of execution for the user in relation to that contract.

The transition is reflected in the transition value or preferably the transition score. In the preferred form, this is the binary score for that contract of that user.

Score 1 is generated when a contract condition that is applicable to the vendor user is fulfilled. If one or more of the terms and conditions applicable to the vendor user are not fulfilled, a score of 0 is generated. More specifically, in this embodiment, the score may be determined by the DFA with the processing of the contract.

In addition, DFA can determine the transaction type, for example, via the details of the transaction or the transaction template used. In this particular embodiment, the transaction is a contract, but the transaction type may be more specific than a particular type of P2P derived contract may be used as the transaction type, for example.

Eventually, DFA comes with the vendor user's bitcoin address for the implementation of the contract. This constitutes attribution information that is characteristic of Bitcoin address in the sense that it is connected with the vendor user. If the user is a paying user, a customer user, DFA will be provided with a public key or signature script that is attribution information in the sense that it is associated with the customer user.

Given this transaction information, this method uses DFA to perform the reputation transaction, which is an additional transaction. In a reputation transaction, DFA provides that the metadata of the reputation transaction includes three metadata in the metadata: the transaction type for the contract; Attribution information related to the contract (eg Bitcoin address or signature script); And fulfillment of such agreements for vendor users (eg, scores).

The DFA then creates a reputation transaction, which in this embodiment is a bitcoin transaction T ₁ , with one of four P2SH multiple signature outputs, 'dust' (a negligible amount of Bitcoin) by the DFA agent. Contains metadata sent to a controlled address. 1 illustrates an implementation of a bitcoin transaction. 2 illustrates a Bitcoin transaction redeem script. 3 illustrates a connection between various transactions. It can be seen that all transactions are standard P2PKH or P2SH multisignature transactions and are valid.

The main advantage of storing reputation information included in such reputation transactions and blockchain is to reduce the possibility of unfair rating attacks because the blockchain cannot be changed. Reputation transactions are themselves useful intermediate forms, but they also allow for the subsequent benefits of the present invention.

In general, before adopting the proposed invention, transaction broadcasts cannot be considered by the DFA mechanism and used to determine reputation information from those transactions. However, each time a Bitcoin transaction is unlocked, the public key is exposed to the signature script, so transaction details associated with that particular public key are always available.

Customer Wallet Use to Extract and Process

The embodiment now returns to the customer user's point of view. In this embodiment, the customer is interested in trading P2P derivatives on the Bitcoin blockchain. As such, including the vendor users reviewed in the above embodiments, they may be provided with multiple transactions from multiple users. The contracts provided may be the same or very similar in terms of format, risk profile, price and other variables between different users providing the transaction.

The customer user's digital wallet allows the customer user to make one or more inquiries. They may be associated with a particular user providing a transaction or with each user providing a transaction of the same type. Using the example of a query for a single user, a customer user is interested in a contract provided by a vendor user. Thus, the customer user can select the vendor user through the wallet function in the customer user's wallet to begin a survey of the vendor user's reputation.

The customer user's wallet is part of the contract being offered, so he knows the bitcoin address of the vendor user providing the transaction. The Bitcoin address is related to the master public key because it is a hash of a specific public key provided by the contract. As a result, the customer user's wallet can determine the vendor user's master public key hash, which is behind some other public key. In this regard, a hash function such as SHA-256 can be used to hash the master public key.

The customer user's wallet can then access and parse the blockchain to retrieve past reputation transactions on the blockchain and filter those transactions by hash of the master key obtained for the selected vendor user. Each reputation transaction in the blockchain using the descendant of the common master public key associated with the selected vendor user in the inquiry by the customer user can be found in this way. Therefore, the wallet extracts reputation information from the blockchain for each transaction linked to the corresponding master public key and thus the vendor user.

After extracting the reputation information, the customer user's wallet can further process the information. For example, the reputation calculation algorithm may perform calculations on the retrieved reputation information, which may yield an aggregate reputation score for the user (s), and the results are displayed in the customer user's wallet. For example, for reputation information for a single user selected, the wallet can consider the total number of pre-reputation transactions that record positive reputation results from the transaction and the total number of pre-reputation transactions that record negative reputation results from the transaction. have. The wallet may indicate a balance of positives and negatives for the customer user with a credit score. The process may assign a relative rating in consideration of information about other users not selected. The process may take into account the total number of reputation transactions that result (if the number is less robust), weight the score, and / or indicate the confidence of the score.

The aggregated reputation scores based on the user via a hash of the master public key may be determined at some point in time, for example, at the time of selection, for presenting the score with suggestions from the user, or before the selection or the user provides a transaction to the customer user. It may be precomputed. The timing may reflect the recent balance of the selected balance or trade off and / or score between speed and accuracy.

The information flow is shown in FIG. As a result of transaction performance by DFA, DFA provides a record of reputation information to the blockchain through additional new reputation transactions. Upon request or request, reputation information flows from the blockchain to the customer user's wallet for processing.

Although the implementation of the present invention is described above in the context of a public key hierarchically derived from a common master public key, the present invention may be implemented in terms of a wallet other than a deterministic wallet. For example, the user has several options to facilitate access. They can: 1) use the same public key for each transaction and use it as the master key, but separate addresses for each transaction (unless it is recommended for security reasons to reuse the same bitcoin address for multiple transactions). It is preferable to produce; 2) using any public key (identified with the same 'master key' each time). However, it is desirable for a user to have a hierarchical deterministic wallet. Because the watt automatically has a master key, it has the inherent advantage of a wallet that users have less to back up).

Use of a DFA in Smart Contracts

This section is intended to provide background on how DFA implements smart contracts. In this example context, a definition is provided for a DFA that models a process or task such as a contract. DFA interacts with a system associated with a computing resource called a computing agent or "bot". This computing agent is configured to create a transaction and submit it to the blockchain. Although this DFA embodiment relates to contracts, the use of DFA is not limited to contracts.

Referring to FIG. 5, an embodiment provides for the realization of the process as a conceptual DFA implemented on a computing platform-blockchain-containing hardware and software components.

5 provides an overview of a system constructed in accordance with an exemplary embodiment of the present invention. The system includes a computing agent 3 that can interact with other entities 4 (eg, human or other computers) to receive instructions. Such commands can, for example, create and execute smart contracts. Thus, computing agent 3 interacts with the physical world to respond to external events in the "real world" and to implement the invention as the cause.

The specification of the contract itself may be provided in any machine execution format, for example xBRL, and is stored in a secure and distributed manner, for example in a distributed hash table (DHT) 5 of the torrent network. From the specification of the contract, the computing agent configures DFA 2, which is then implemented in blockchain 1 by one or more agents.

DFA 2 itself is designated as a finite set {S, I, t, s0, F}, where S represents the state of a possible (finite) set that can be a contract / DFA; I is a (finite) set of inputs (also known as alphabetical), meaning any event or condition that may occur in connection with the contract, such as payment, maturity of the device, default of the other party, etc .; In our mechanism these input signals are received / produced by one or more agents and determine the next state (possibly the same) of the system.

The third component of DFA is the transition function t: SХI → S. The term "deterministic" in "DFA" refers to the uniqueness of a decision: only one new state (probably the same), given a state and an input. Thus, given the initial state S ₀ and the input history, the result of the calculation (contract) is unique to one of all possible final result sets F⊆S. Once all these elements are set, the DFA is fully defined by a transition table that specifies the future state for all possible current states and input signals. The state of DFA is related to transaction output (UTXO) not used in the blockchain. As is known in the art, the Bitcoin network keeps track of all available UTXOs. According to an embodiment, the mechanism by which the DFA moves from one state to another is implemented (executed) by a blockchain transaction in accordance with the present invention. Effectively, transactions in the blockchain consume UTXOs associated with one state (the input of the previous transaction) and generate UTXOs associated with the next state (output).

Example: Discount (Zero-Coupon) Bond

To illustrate, we now consider discount (zero-coupon) bonds, which are simple bonds that are purchased at a price (usually discounted to face value) and held until the principal is returned at maturity. The possible states we consider are S = {s ₀ , f ₀ , f ₁ }, respectively, holding state (s ₀ ), (if following a happy path) normal conclusion or happy ending of the contract (f ₀ ), litigation respectively. It shows a state (f ₁₎ that status is invalid, such as. Thus, the final state of the system is F = {f ₀ , f ₁ }. The alphabets we will consider are I = {r, d, e}, each with the repayment of principal (r) at maturity (r), the failure of the issuer (d) at maturity (d), and without repayment. Indicates expiration of contract (e). The transition matrix for such a simple contract is shown in Table 1.

t r d e s ₀ f ₀ f ₁ f ₁

Table 1 is a transition table for DFA representing a zero-coupon bond.

The final status indicates the completion of the contract, so you no longer need to specify the status (currently indicated by a '-' in the transition table, but the line may be omitted). In principle, more states and / or inputs (as well as actions) may be defined for the device, but rather to provide a concise and clear description of the underlying inventive aspects of the present invention rather than to provide details about complex contracts. Did not perform.

6 shows an embodiment of a zero-coupon bond DFA on the (Bitcoin) blockchain. The state is represented by a circle and a bitcoin transaction that moves a machine from one state to another in a triangle. The input received by the agent is omitted in FIG. 6 but one or another transition must occur in each state depending on this input. This is reflected in the diagram by the construction of one or another bitcoin transaction (eg, state s ₀ to t ₀ or t ₁ ); The transition that does not change state is omitted because no transaction is required. In addition to DFA's transition transaction t _i , the initial original transaction o and the transaction ci corresponding to the completion of the contract are considered.

We now pay attention to the flow of funds in transactions (start, transfer and completion). An important observation is that due to the finite nature of DFA and (financial) contracts, the process is completed after several transitions. This essentially means that the maximum cost of establishing and executing the contract is fixed (assuming a small fee for the associated computing agent and Bitcoin miner), and can be predetermined at the time of establishment of the DFA. It is offered as the total amount needed to execute the contract along the longest path imaginable. This, of course, excludes the possibility of infinite loops in execution. However, this is not related to current (financial) contracts, and despite their name, permanent contracts can be completed at some point in the future; For example, a debt entity may no longer exist or payment may be ignored due to inflation.

The foregoing embodiments illustrate rather than limit the invention, and it should be understood by those skilled in the art that many alternative embodiments may be designed without departing from the scope of the invention as defined by the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The words "comprising" and "comprises" and the like do not exclude the presence of a configuration or step listed in the claims or the specification. In this specification, "comprises" means "includes or consist of" and "comprising" means "including or consisting of". . A single reference number in a configuration does not exclude multiple reference numbers in this configuration and vice versa. The invention may be implemented by hardware including several distinct configurations and by a suitably programmed computer. In the device claim enumerating several means, several of these means may be embodied by one and the same hardware item. The simple fact that a particular measurement is quoted in different dependent terms does not mean that a combination of these measurements cannot be utilized.

Claims (20)

A method of computing aggregated user related data, the method comprising:
a. Constructing a user related data transaction, wherein the user related data transaction comprises an expression of user related data from a previous transaction associated with a user;
b. Broadcasting the user-related data transaction to the blockchain;
c. Repeating steps a) and b) for the plurality of previous transactions and / or the plurality of users;
d. Selecting a user for which aggregated user related data is required to obtain a selected user;
e. Creating a filter associated with the selected user;
f. Retrieving a blockchain for a user related data transaction to which the filter is applied;
g. Computing aggregated user related data for the selected user from the user related data transactions to which the filter is applied. The method of claim 1,
a. Defining a transaction between at least one user and at least one other user;
b. Executing the transaction;
c. Providing a user related data representation by providing user related data from the transaction for at least one user or at least one other users; Provide one or more of
Providing a user related data representation for use in constructing a user related data transaction, wherein the user related data transaction comprises a user related data representation. A method of computing aggregated user related data,
a. Selecting a user for which aggregated user related data is required to obtain a selected user;
b. Creating a filter associated with the selected user;
c. Retrieving a blockchain for a user related data transaction to which the filter is applied;
d. Computing aggregated user related data for the selected user from the user related data transactions to which the filter is applied. The method according to any one of claims 1 to 3,
Further providing an evaluation of the computed aggregated user related data, wherein the evaluation provides a decision and / or an action and / or a modification. The method of claim 4, wherein
Decisions and / or actions and / or modifications
a. Change to one or more inputs to one or more additional transactions, such as blockchain transactions;
b. Change to one or more outputs from one or more additional transactions, such as blockchain transactions;
c. Change to DFA, such as DFA, which implements one or more additional transactions
To generate one or more of the following. The method according to claim 4 or 5,
Decisions and / or actions and / or modifications
a. Feedback to modify and / or optimize the design and / or production and / or storage and / or distribution and / or consumption of services and / or products;
b. Feedback to modify and / or optimize processes, such as those for the design and / or production and / or storage and / or distribution and / or consumption of services and / or products
To provide one or more of the following. The method according to any one of claims 4 to 6,
Decisions and / or actions and / or modifications provide a feedback for modifying and / or optimizing a contract, such as a smart contract. The method according to any one of claims 1 to 7,
The user is selected from users providing a transaction. The method according to any one of claims 1 to 8,
And the filter is configured from an address hash that results from the public key of the selected user. The method according to any one of claims 1 to 9,
The filter is configured from a signature script originating from the public key of the selected user. The method according to any one of claims 1 to 10,
The filter is a hash of a master public key of the selected user. The method according to any one of claims 1 to 11,
And the filter collects all reputation transactions including metadata about the master public key and all their descendant public keys for the selected user. The method according to any one of claims 1 to 12,
The choices are made using your digital wallet. The method according to claim 16 or 16, wherein
The method includes selecting a plurality of users and computing aggregated user related data for each of the plurality of users. A system set up to implement the method of claim 1. The method of claim 15,
The system is:
a. User digital wallet;
b. At least one computing agent configured to implement DFA through a blockchain;
c. A system that includes a blockchain platform. A system set up to implement a method according to claim 3. The method of claim 17,
The system is:
c) at least one computing agent configured to implement DFA through a blockchain;
d) a system that includes a blockchain platform In the method of making a record of user-related data,
a. Defining a transaction between at least one user and at least one other user;
b. Implementing the transaction;
c. Providing a user related data representation by providing user related data from the transaction by at least one user or at least one other user;
d. Constructing a user related data transaction comprising the user related data representation;
e. Broadcasting a user-related data transaction to the blockchain. A system set up to implement the method of claim 19.

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